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Regime switching models for circular and linear time series

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  • Andrew Harvey
  • Dario Palumbo

Abstract

The score‐driven approach to time series modelling is able to handle circular data and switching regimes with intra‐regime dynamics. Furthermore it enables a dynamic model to be fitted to a linear and a circular variable when their joint distribution is a cylinder. The viability of the new method is illustrated by estimating models for hourly data on wind direction and speed in Galicia, north‐west Spain. The modelling of intra‐regime dynamics is shown to be of critical importance.

Suggested Citation

  • Andrew Harvey & Dario Palumbo, 2023. "Regime switching models for circular and linear time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(4), pages 374-392, July.
    • Handle: RePEc:bla:jtsera:v:44:y:2023:i:4:p:374-392
    DOI: 10.1111/jtsa.12678
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    References listed on IDEAS

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    Cited by:

    1. Blazsek, Szabolcs & Kong, Dejun & Shadoff, Samantha R., 2025. "Within-regime volatility dynamics for observable- and Markov-switching score-driven models," Finance Research Letters, Elsevier, vol. 73(C).
    2. Frederik Krabbe, 2024. "Asymptotic Properties of the Maximum Likelihood Estimator for Markov-switching Observation-driven Models," Papers 2412.19555, arXiv.org, revised Dec 2025.

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